PowerNet: Transferable Dynamic IR Drop Estimation via Maximum Convolutional Neural Network

• Published in: Proceedings of the ASP-DAC ... Asia and South Pacific Design Automation Conference pp. 13 - 18
• Main Authors: Xie, Zhiyao, Ren, Haoxing, Khailany, Brucek, Sheng, Ye, Santosh, Santosh, Hu, Jiang, Chen, Yiran
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.01.2020
• Subjects: Convolutional neural networks; Design automation; Machine learning; Maximum likelihood estimation; Power grids; Power system dynamics

IR drop is a fundamental constraint required by almost all chip designs. However, its evaluation usually takes a long time that hinders mitigation techniques for fixing its violations. In this work, we develop a fast dynamic IR drop estimation technique, named PowerNet, based on a convolutional neur...